• DocumentCode
    2498881
  • Title

    Novel VNS Algorithms on Asymmetric Traveling Salesman Problems

  • Author

    Piriyaniti, Ittiporn ; Pongchairerks, Pisut

  • Author_Institution
    Ind. Eng. Program, Thammasat Univ., Pathumthani, Thailand
  • fYear
    2010
  • fDate
    23-25 April 2010
  • Firstpage
    407
  • Lastpage
    409
  • Abstract
    The Asymmetric Traveling Salesman Problem (ATSP) is one of the most studied combinatorial optimization problems. It is a generalized traveling salesman problem in which distances between a pair of cities need not equal in the opposite direction. Since ATSP belongs to a class of NP-hard problems and the optimal solution cannot be found within an appropriate computation time, many researchers have thus paid their attentions to develop effective heuristics to find out good solutions within a short computation time. This paper proposes various VNS algorithms for ATSP in order to find out for the best algorithm among them. Each of these VNS algorithms is developed based on a distinct combination of neighborhood. In order to compare the performances of the VNS algorithms proposed in this research, these VNS algorithms are run on the benchmark ATSP instances, and the results taken from these algorithms are then compared in terms of solution quality.
  • Keywords
    combinatorial mathematics; computational complexity; optimisation; travelling salesman problems; ATSP; NP-hard problems; VNS algorithms; asymmetric traveling salesman problems; combinatorial optimization problems; Cities and towns; Computer networks; Genetic algorithms; Industrial engineering; NP-hard problem; Optimization methods; Routing; Search methods; Traveling salesman problems; Vehicles; Asymmetric Traveling Salesman Problem; Combinatorial Optimization Problem; NP-hard; Variable Neighborhood Search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Network Technology (ICCNT), 2010 Second International Conference on
  • Conference_Location
    Bangkok
  • Print_ISBN
    978-0-7695-4042-9
  • Electronic_ISBN
    978-1-4244-6962-8
  • Type

    conf

  • DOI
    10.1109/ICCNT.2010.75
  • Filename
    5474465